This volume presents the latest research in probabilistic graphical models from leading international experts. The 38 revised full papers included were selected from 44 submissions, reflecting a rigorous review process. The proceedings cover a wide array of topics within graphical models, including reasoning, decision-making, and learning. This collection serves as a valuable resource for researchers and practitioners in the field.

This collection of papers from the 7th International Workshop on Probabilistic Graphical Models offers a snapshot of current research in the field. The selection process, involving 38 revised full papers from 44 submissions, suggests a high standard for the included work. The papers collectively address core areas of graphical models, including reasoning, decision-making, and learning. This proceedings volume is likely to be of interest to academics and professionals specializing in artificial intelligence and machine learning.